Bridging the gaps in pediatric complex healthcare: the case for home nursing care among children with medical complexity.

BACKGROUND: Children with medical complexity (CMC) comprise < 1% of the pediatric population, but account for nearly one-third of healthcare expenditures. Further, while CMC account for up to 80% of pediatric inpatient hospital costs, only 2% of Medicaid spending is attributed to home healthcare. As a result, the current health system heavily relies on family caregivers to fill existing care gaps. This study aimed to: (1) examine factors associated with hospital admissions among CMC and (2) contextualize the potential for home nursing care to improve outcomes among CMC and their families in South Carolina (SC). METHODS: This mixed-methods study was conducted among CMC, their family caregivers, and physicians in SC. Electronic health records data from a primary care clinic within a large health system (7/1/2022-6/30/2023) was analyzed. Logistic regression examined factors associated with hospitalizations among CMC. In-depth interviews (N = 15) were conducted among physicians and caregivers of CMC statewide. Patient-level quantitative data is triangulated with conceptual findings from interviews. RESULTS: Overall, 39.87% of CMC experienced ≥ 1 hospitalization in the past 12 months. CMC with higher hospitalization risk were dependent on respiratory or neurological/neuromuscular medical devices, not non-Hispanic White, and demonstrated higher healthcare utilization. Interview findings contextualized efforts to reduce hospitalizations, and suggested adaptations related to capacity and willingness to provide complex care for CMC and their families. CONCLUSIONS: Findings may inform multi-level solutions for accessible, high-quality home nursing care among CMC and their families. Providers may learn from caregivers' insight to emphasize family-centered care practices, acknowledging time and financial constraints while optimizing the quality of medical care provided in the home.

Examining Patient- and Community-Level Factors Associated with Pediatric Mental Healthcare Access Within a Patient Navigation Program.

In 2021, national leaders in the United States declared a "national youth mental health crisis." Still, only 1-in-4 children receive adequate mental healthcare access. Patient Navigator Programs (PNPs) can improve children's referral-to-connection to mental health services. We examined patient- and community-level factors associated with pediatric mental healthcare access. Pediatric Support Services (PSS) is a PNP that triages mental and behavioral health referrals within a large health system in a southeastern state. This study analyzes PSS data from September 2017-March 2023 and Child Opportunity Index 2.0 state-normed zip-code level data to assess social drivers of health estimates. Structural equation modeling was conducted between patient- and community-level factors and connection to mental health services. Overall, 62.7% of children connected to mental health services since PSS' inception. Regardless of SDOH, as children get older, they are more likely to connect with mental health services (ß = .053, SE = .010, p < .001). Children with greater number of referral needs are more likely to connect with mental health services (ß = .034, SE = .011, p = .002). Further, children who live in communities with higher opportunity levels are more likely to connect with mental health services (ß = .016, SE = .008, p = .040), suggesting that children who live in low-income communities experience more barriers to mental healthcare. Social drivers may inform referral practices and tiered navigation support for optimal mental healthcare access among children. Further research should demonstrate the effectiveness of PNPs integrated within healthcare and community-based settings.

Identifying Risk Factors Associated with Repeated Referrals Within a Pediatric Navigation Program.

Approximately 1-in-5 children have a diagnosed mental, behavioral, and/or developmental disorder or delay by age 8 in the United States. Children with such conditions often require complex, complicated diagnostic and specialty care, making them susceptible to repeated referrals and ongoing unmet healthcare needs. Patient navigation programs (PNPs) are designed to integrate care from primary care providers to community-based services, using trained navigators to help patients and their families manage referrals and connect with referred services. This study examines factors associated with repeated referrals to an active PNP to inform ongoing referral patterns and adaptations to standard navigation support within a large healthcare system in South Carolina (SC). Data is sourced from the inception of the PNP in 2017 through 2022, including 15,702 referrals. Overall, 71.07% had no repeated referrals. Children who are older, diagnosed with attention deficit disorder(s), behavioral concerns, depression, multiple referral needs, and insured by Medicaid were found to be most susceptible to repeated referrals. Conversely, children who are non-Hispanic Black, were referred at a well-child visit, and are primarily insured by private insurance or Tricare were least likely to have repeated referrals. Children who are insured by Medicaid are more likely to be younger, identify as non-Hispanic Black, Hispanic, or another race/ethnicity, and have multiple needs at time of initial referral, identifying a potentially compounded risk for those who hold multiple risk factors to experiencing repeated referrals. Findings may inform adaptations to this PNP model to adjust navigator protocol for at-risk populations and equitably optimize referral-to-service connection.

Community features' varying insight into emergency department use for different childhood injuries.

BACKGROUND: Community-level factors, including poverty level, minority population, and rurality are predictive of child injury rates. Community-based interventions targeting high-risk communities have been suggested for prevention and are reliant on understanding details of the community and prevalent types of injuries. The present study assessed injury rates based on characteristics of the community and for different types of injuries. METHOD: A retrospective review of emergency department visits identified zip-code and injury type data for children 0-19. Injuries related to bicycles, falls, motor-vehicle traffic (MTV), and violence were examined. Poverty level, minority population, rural classification, and insured population were obtained at the zip-code level. Regression models examined the association between community features and injury rates for the four categories of injuries. RESULTS: The results showed that the relationship between community features and injury rates was dependent on injury type. Rurality was associated with a lower rate for bicycle and falls, but a higher rate of MVT; higher insured population was associated with higher MVT and violence rates; higher minority population was associated with lower rates for falls and MTV; and higher population in poverty was associated with lower rate for MTV. CONCLUSIONS: The findings indicate that injury rates not only cluster among community-level characteristics, but also the type of injury. Variation in community features and injury types offer insight into a holistic approach to child health. PRACTICAL APPLICATIONS: In addition to other factors related to risk for injuries, health providers' knowledge of features of the local community and prevalent injuries in the environment may be helpful additions to programming geared toward lessening the burden of injuries on children and healthcare systems.

School-Based Mental Health Service Utilization Through the COVID-19 Pandemic and Beyond.

BACKGROUND: We examined trends in mental health service utilization before, during, and in the immediate return to in-person learning throughout the COVID-19 pandemic. METHODS: Retrospective chart review was assessed for changes in odds of any visit being a mental health encounter from five school-based health centers from the 2018-2019 to the 2021-2022 school years. Data are limited to the in-person school year from mid-August to early June. RESULTS: Data were assessed from 1239 students seen through 2256 visits over the 4 school years (Mage = 12.93). The odds of any visit being related to a mental health encounter increased each school year, with the 2020 to 2021 and 2021 to 2022 school years having significant increases in odds (both compared to the first and to the antecedent school year). In addition, during the 2019 to 2020 and 2020 to 2021 school years, the odds of a repeated mental health encounter significantly increased from year to year. CONCLUSIONS: Findings indicate a steadily increasing number of mental health service utilization needs among adolescent students that was significantly exponentiated throughout the COVID-19 pandemic.

"I Don't Want to Go to Work": A Mixed-Methods Analysis of Healthcare Worker Experiences from the Front- and Side-Lines of COVID-19.

During the COVID-19 pandemic, healthcare workers (HCW) were categorized as "essential" and "non-essential", creating a division where some were "locked-in" a system with little ability to prepare for or control the oncoming crisis. Others were "locked-out" regardless of whether their skills might be useful. The purpose of this study was to systematically gather data over the course of the COVID-19 pandemic from HCW through an interprofessional lens to examine experiences of locked-out HCW. This convergent parallel mixed-methods study captured perspectives representing nearly two dozen professions through a survey, administered via social media, and video blogs. Analysis included logistic regression models of differences in outcome measures by professional category and Rapid Identification of Themes from Audio recordings (RITA) of video blogs. We collected 1299 baseline responses from 15 April 2020 to 16 March 2021. Of those responses, 12.1% reported no signs of burnout, while 21.9% reported four or more signs. Qualitative analysis identified four themes: (1) professional identity, (2) intrinsic stressors, (3) extrinsic factors, and (4) coping strategies. There are some differences in the experiences of locked-in and locked-out HCW. This did not always lead to differing reports of moral distress and burnout, and both groups struggled to cope with the realities of the pandemic.

Predictive value of clinical symptoms for COVID-19 diagnosis in young adults.

Objective: Assessment of predictive values of clinical symptoms for COVID-19 diagnosis in young adults. Participants: Nonresidential university students (ages 18-25) participating in surveillance testing and mandatory symptom survey between 9/9/2020 and 11/25/2020. Methods: Retrospective study of test results and symptom survey data. Results: Among 6,489 individuals, 288 (4.4%) tested positive for COVID-19, 90 (31.3%) of whom reported symptoms. COVID-19 prevalence among individuals reporting and not reporting symptoms was 17.2% and 3.3%, respectively. The four symptoms with highest positive predictive values (PPVs) were smell/taste loss (PPV = 38.5%), chills (PPV = 31.5%), muscle/joint pain (PPV = 26.0%), and fever (PPV = 25.9%). Conclusions: Institutions should emphasize COVID-19 risk for highly predictive symptoms in public health messaging to inform individuals on when to seek testing or self-isolation. However, low COVID-19 diagnostic accuracy of clinical symptoms and the high pre-symptomatic/asymptomatic rate (69%) highlight the limitations of voluntary testing strategies employed by higher education institutions during the original strain of SARS-CoV-2.